Analysis of Kano-model-based customer needs for product development

• Published in: Systems engineering Vol. 14; no. 2; pp. 154 - 172
• Main Authors: Sharif Ullah, A. M. M., Tamaki, Jun'ichi
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.06.2011; Wiley
• Subjects: Agglomeration; Applied sciences; Computer science; control theory; systems; Computer simulation; customer needs; Demographics; Exact sciences and technology; information content; Information theory; Information, signal and communications theory; Kano model; Mathematical models; Product development; Quantitative analysis; Software; Software engineering; Telecommunications and information theory; Uncertainty; Voice; Data type; Weighted average; Demography; uncertainty; Mean estimation; Modeling; Aggregation; Information measure; Uncertain system; Weighting; information content; Preference; Kano model; User requirement; Product development; customer needs; Quantitative analysis
• ISSN: 1098-1241; 1520-6858
• DOI: 10.1002/sys.20168

The Kano model is a useful model for integrating the Voice of the Customer into the subsequent processes of product development. This paper presents a method for analyzing customers' preferences obtained by using the Kano model. In the Kano model, customers' preferences are obtained by using a prescribed form to know whether or not a given product attribute is a Must‐be, Attractive, One‐dimensional, Indifferent, or Reverse attribute for a given product. Since the preference may vary a lot from customer to customer due to the demographic and psychographic factors, a quantitative aggregation process is needed to compute the information content of all customer answers and finally to decide the aforementioned status of each product attribute. Most of the quantitative methods developed so far deal mainly with the imprecision in the customer answers and do not address the uncertain (unknown or missing) customer answers. In fact, a significant number of customers might not be able to submit their answers on time. As a result, a significant number of answers remain unknown that manifests a great deal of uncertainty. This paper shows an approach to simulate the unknown customer answers. In addition, an approach is developed to measure the information content of customer answers integrating the real and simulated customer answers. This is helpful for identifying the correct status (Must‐be, Attractive, One‐dimensional, Indifferent, or Reverse) of each product attribute. Moreover, it is shown that the weighted average type of quantitative analysis is not suitable for quantifying the inherent complexity of customer answers obtained in accordance with the Kano model. © 2010 Wiley Periodicals, Inc. Syst Eng 14: 154–172, 2011